I chatted with Kessels and Wittens on the #drupal IRC channel this afternoon, and found out that personalized tag clouds are also on Kessels' development track. I'm still pushing group tag clouds created from different user profile identities (i.e. creating tag clouds for the tags from anti-war and pro-war identified users). More details in the 2nd & 3rd flowcharts here.

Wittens also reported that he's implementing a one-line tag cloud query in MySQL:

UPDATE 5-24-06: I have now included the source data for the charts below including term id, term name & frequency

This post is a follow-up to the previous posts here, here and here with more information on an algorithm for automating the font distribution for a Drupal tag cloud. There's also an optional alteration that would evenly distribute the font sizes across a Power Law tag frequency distribution.

I'll step through the details below with the intention of following up with some Drupal developers who will be able to code this up in PHP and provide it to the Drupal community as a module -- most likely this module could be built on top of the tagadelic module.

This has been my first attempt at specifying additional Drupal functionality in preparation for specifying other aspects of my Development Roadmap.

Being able to automatically create tag clouds, personal tag clouds and tag clouds based upon user-specified identities will be a very useful tool for visualizing the subjective context and qualitative opinions that volunteers have about interview sound bites.

My intent is to get this tag cloud development rolling to build momentum for the other aspects of the Phase 01 of my roadmap.

The remaining aspects of this post are pretty technical, but I'll include some graphics below for anyone else interested in following along...

I created a tag cloud for my website, and I'd like to see this feature added as a dynamic Drupal module. I thought I'd briefly go through the steps that I went through to give a leg up for anyone who wants to code this up in PHP.

The hardest part is the algorithm that automatically determines the distribution of font sizes based upon the frequency distribution of tags.